class_docstr: Depthwise separable conv.
  DilConv(dilation=1) * 2.
code: def __init__(
      self, C_in, C_out, kernel_size, stride, padding, affine=True
  ):
      super().__init__()
      self.net = nn.Sequential(
          DilConv(
              C_in,
              C_in,
              kernel_size,
              stride,
              padding,
              dilation=1,
              affine=affine,
          ),
          DilConv(
              C_in,
              C_out,
              kernel_size,
              1,
              padding,
              dilation=1,
              affine=affine,
          ),
      )
  
imports: import torch
  import torch.nn
label_desc: Use image node_id 1 to create a new SepConv object from inherited base classes: nn with example: obj = SepConv(C_in, C_out, kernel_size, stride, padding, affine)